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Manually-parcellated gyral data accounting for all known anatomical variability

Morphometric brain changes occur throughout the lifetime and are often investigated to understand healthy ageing and disease, to identify novel biomarkers, and to classify patient groups. Yet, to accurately characterise such changes, an accurate parcellation of the brain must be achieved. Here, we p...

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Detalles Bibliográficos
Autores principales: Mikhael, Shadia S., Mair, Grant, Valdes-Hernandez, Maria, Hoogendoorn, Corné, Wardlaw, Joanna M., Bastin, Mark E., Pernet, Cyril
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6350632/
https://www.ncbi.nlm.nih.gov/pubmed/30694228
http://dx.doi.org/10.1038/sdata.2019.1
Descripción
Sumario:Morphometric brain changes occur throughout the lifetime and are often investigated to understand healthy ageing and disease, to identify novel biomarkers, and to classify patient groups. Yet, to accurately characterise such changes, an accurate parcellation of the brain must be achieved. Here, we present a manually-parcellated dataset of the superior frontal, the supramarginal, and the cingulate gyri of 10 healthy middle-aged subjects along with a fully detailed protocol based on two anatomical atlases. Gyral parcels were hand-drawn then reviewed by specialists blinded from the protocol to ensure consistency. Importantly, we follow a procedure that allows accounting for anatomical variability beyond what is usually achieved by standard analysis packages and avoids mutually referring to neighbouring gyri when defining gyral edges. We also provide grey matter thickness, grey matter volume, and white matter surface area information for each parcel. This dataset and corresponding measurements are useful in assessing the accuracy of equivalent parcels and metrics generated by image analysis tools and their impact on morphometric studies.